Quantifying cell-type proportions and their corresponding gene expression profiles in tissue samples would enhance understanding of the contributions of individual cell types to the physiological states of the tissue. Current approaches that address ...
Techniques using machine learning for short term blood glucose level prediction in patients with Type 1 Diabetes are investigated. This problem is significant for the development of effective artificial pancreas technology so accurate alerts (e.g. hy...
The International journal of neuroscience
Dec 1, 2019
: The newborn brain MRI (magnetic resonance imaging) tissue segmentation plays a vital part in assessment of primary brain growth. In the newborn stage (nearly less than 28 days old), in T1- as well as T2-weighted MR images similar levels of intensit...
Asian Pacific journal of cancer prevention : APJCP
Dec 1, 2019
OBJECTIVE: The death rate of breast tumour is falling as there is progress in its research area. However, it is the most common disease among women. It is a great challenge in designing a machine learning model to evaluate the performance of the clas...
Canadian journal of surgery. Journal canadien de chirurgie
Dec 1, 2019
Providing the earliest hemorrhage control is now recognized as a shared responsibility of all members of society, including both the lay public and professionals, consistent with the Stop the Bleed campaign. However, providing early hemorrhage contro...
Neural networks : the official journal of the International Neural Network Society
Nov 30, 2019
Humans perceive physical properties such as motion and elastic force by observing objects in visual scenes. Recent research has proven that computers are capable of inferring physical properties from camera images like humans. However, few studies pe...
Neural networks : the official journal of the International Neural Network Society
Nov 30, 2019
A deep learning classifier for detecting seizures in neonates is proposed. This architecture is designed to detect seizure events from raw electroencephalogram (EEG) signals as opposed to the state-of-the-art hand engineered feature-based representat...
Traditional general linear model-based brain mapping efforts using functional neuroimaging are complemented by more recent multivariate pattern analyses (MVPA) that apply machine learning techniques to identify the cognitive states associated with re...
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